metadata
base_model: google/gemma-3-270m-it
license: gemma
tags:
- gemma3
- gemma
- google
- mlx
pipeline_tag: text-generation
library_name: mlx
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
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Google’s usage license. To do this, please ensure you’re logged in to Hugging
Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
sionic-ai/mlx-gemma-3-270m-it
This model sionic-ai/mlx-gemma-3-270m-it was converted to MLX format from google/gemma-3-270m-it using mlx-lm version 0.26.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("sionic-ai/mlx-gemma-3-270m-it")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)